27,529 research outputs found

    Automatically Discovering, Reporting and Reproducing Android Application Crashes

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    Mobile developers face unique challenges when detecting and reporting crashes in apps due to their prevailing GUI event-driven nature and additional sources of inputs (e.g., sensor readings). To support developers in these tasks, we introduce a novel, automated approach called CRASHSCOPE. This tool explores a given Android app using systematic input generation, according to several strategies informed by static and dynamic analyses, with the intrinsic goal of triggering crashes. When a crash is detected, CRASHSCOPE generates an augmented crash report containing screenshots, detailed crash reproduction steps, the captured exception stack trace, and a fully replayable script that automatically reproduces the crash on a target device(s). We evaluated CRASHSCOPE's effectiveness in discovering crashes as compared to five state-of-the-art Android input generation tools on 61 applications. The results demonstrate that CRASHSCOPE performs about as well as current tools for detecting crashes and provides more detailed fault information. Additionally, in a study analyzing eight real-world Android app crashes, we found that CRASHSCOPE's reports are easily readable and allow for reliable reproduction of crashes by presenting more explicit information than human written reports.Comment: 12 pages, in Proceedings of 9th IEEE International Conference on Software Testing, Verification and Validation (ICST'16), Chicago, IL, April 10-15, 2016, pp. 33-4

    Incident detection using data from social media

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    This is an accepted manuscript of an article published by IEEE in 2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC) on 15/03/2018, available online: https://ieeexplore.ieee.org/document/8317967/citations#citations The accepted version of the publication may differ from the final published version.© 2017 IEEE. Due to the rapid growth of population in the last 20 years, an increased number of instances of heavy recurrent traffic congestion has been observed in cities around the world. This rise in traffic has led to greater numbers of traffic incidents and subsequent growth of non-recurrent congestion. Existing incident detection techniques are limited to the use of sensors in the transportation network. In this paper, we analyze the potential of Twitter for supporting real-time incident detection in the United Kingdom (UK). We present a methodology for retrieving, processing, and classifying public tweets by combining Natural Language Processing (NLP) techniques with a Support Vector Machine algorithm (SVM) for text classification. Our approach can detect traffic related tweets with an accuracy of 88.27%.Published versio

    Overcoming Language Dichotomies: Toward Effective Program Comprehension for Mobile App Development

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    Mobile devices and platforms have become an established target for modern software developers due to performant hardware and a large and growing user base numbering in the billions. Despite their popularity, the software development process for mobile apps comes with a set of unique, domain-specific challenges rooted in program comprehension. Many of these challenges stem from developer difficulties in reasoning about different representations of a program, a phenomenon we define as a "language dichotomy". In this paper, we reflect upon the various language dichotomies that contribute to open problems in program comprehension and development for mobile apps. Furthermore, to help guide the research community towards effective solutions for these problems, we provide a roadmap of directions for future work.Comment: Invited Keynote Paper for the 26th IEEE/ACM International Conference on Program Comprehension (ICPC'18

    Integrating Diplomacy and Social Media: A Report of the First Annual Aspen Institute Dialogue on Diplomacy and Technology

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    This report is a result of the first annual Aspen Institute Dialogue on Diplomacy and Technology, or what we call ADDTech. The concept for this Dialogue originated with longtime communications executive and Aspen Institute Trustee Marc Nathanson. Since his tenure as Chairman of the U.S. Broadcasting Board of Governors (BBG), Nathanson has been concerned with how American diplomacy could more rapidly embrace the changing world of social media and other technologies. He is also a graduate of the University of Denver where former Secretary of State Madeleine Albright's father, Josef Korbel, namesake of the Josef Korbel School of International Relations there, was his professor. Thus, Albright, another Institute Trustee, was a natural partner to create the first Dialogue on Diplomacy and Technology. The cast is ably supplemented with Korbel School Dean and former U.S. Ambassador Christopher Hill and Aspen Institute President Walter Isaacson, who himself was also recently the chair of the BBG.The topic for this inaugural dialogue is how the diplomatic realm could better utilize new communications technologies. The group focused particularly on social media, but needed to differentiate among the various diplomacies in play in the current world, viz., formal state diplomacy, public diplomacy, citizen diplomacy and business diplomacy. Each presents its own array of opportunities as well as problems. In this first Dialogue, much of the time necessarily had to be used to define our terms and learn how technologies are currently being used in each case. To help us in that endeavor, we focused on the Middle East. While the resulting recommendations are therefore rather modest, they set up the series of dialogues to come in the years ahead
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